CN102800072B - Diasonograph scan image quality optimization disposal route and device thereof - Google Patents
Diasonograph scan image quality optimization disposal route and device thereof Download PDFInfo
- Publication number
- CN102800072B CN102800072B CN201210205578.1A CN201210205578A CN102800072B CN 102800072 B CN102800072 B CN 102800072B CN 201210205578 A CN201210205578 A CN 201210205578A CN 102800072 B CN102800072 B CN 102800072B
- Authority
- CN
- China
- Prior art keywords
- subimage
- image
- optimization
- scan image
- optimized
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Landscapes
- Ultra Sonic Daignosis Equipment (AREA)
- Image Processing (AREA)
Abstract
The present invention relates to a kind of picture quality optimized treatment method and device thereof, especially a kind of diasonograph scan image quality optimization disposal route and device thereof.According to technical scheme provided by the invention, a kind of diasonograph scan image quality optimization disposal route, described scan image quality optimization disposal route comprises the steps: a, input scan image, and carries out pre-service to described scan image, so that scan image is divided into some subimages; B, the subimage after above-mentioned segmentation walked abreast and carries out required image optimization process, optimized subimage accordingly after each subimage optimization, and optimization subimage corresponding for described each subimage is merged into an optimized image; C, all optimized image obtained above is merged after export.The present invention can improve medical supersonic scan image quality effectively; Can remove or reduce speckle noise, strengthening organ organizational boundary, improve spatial resolution and strengthen contrast.
Description
Technical field
The present invention relates to a kind of picture quality optimized treatment method and device thereof, especially a kind of diasonograph scan image quality optimization disposal route and device thereof, belong to the technical field of diasonograph image procossing.
Background technology
Ultrasonic detecting technology, as a kind of diagnostic means, is applied to human body by diagnostic ultrasonic equipment, by measuring data and the form of understanding Human Physiology institutional framework to be measured, to reach the object finding disease.
The scan image obtained in instrument scanning process, for doctor makes a definite diagnosis patient disease, plays an important reference role.Can say, the image that scanning obtains is more clear, and picture quality is higher, and doctor more can accurately judge the situation of patient.
And the scan image that current diagnostic equipment obtains, after carrying out hardware image real time transfer, the display image finally shown, then more or less can have some defects.Such as, when process smoothing to image, visual some parts just may be made to seem fuzzy and lack the detailed information of some images.When carrying out edge strengthening process to image, display image may will be made to produce speckle noise.And Combined Processing is carried out to image, then significantly may reduce image frame rate.
In sum, a kind of new diasonograph scan image optimized treatment method of necessary exploitation, overcomes defect of the prior art.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, provide a kind of diasonograph scan image quality optimization disposal route and device thereof, it can optimize the effect of scan image effectively, improves scan image display quality.
According to technical scheme provided by the invention, a kind of diasonograph scan image quality optimization disposal route, described scan image quality optimization disposal route comprises the steps:
A, input scan image, and pre-service is carried out to described scan image, so that scan image is divided into some subimages;
B, the subimage after above-mentioned segmentation walked abreast and carries out required image optimization process, optimized subimage accordingly after each subimage optimization, and optimization subimage corresponding for described each subimage is merged into an optimized image;
C, all optimized image obtained above is merged after export.
Further, in described step a, when pre-service is carried out to scan image, scan image is amplified according to the first predetermined ratio, and the image after amplification is divided into the subimage of more than 3 or 3 according to the second predetermined ratio.
Further, the specification of subimage is divided into be equal-specification or one or both not in equal-specification described in.
Further, in described step a, scan image is amplified with border mapping mode under the first predetermined ratio.
Further, in described step b, to the subimage be divided into be optimized processing mode comprise that drawing is level and smooth, border strengthens or GTG than at least two kinds in strengthening; The be optimized quantity of subimage of each subimage is consistent with the optimization process mode type of employing.
Further, in described step c, by nonlinear weight, optimized image is merged.
A kind of diasonograph scan image quality optimization treating apparatus, comprise pretreatment unit, described pretreatment unit is connected with optimization process unit, and described optimization process unit is connected with image composing unit; Pretreatment unit is to scan image pre-service, and pretreated Iamge Segmentation is become some subimages, above-mentioned subimage walks abreast and carries out required image optimization process by optimization process unit, to obtain the optimization subimage of respective numbers after making each subimage optimization; The optimization subimage of above-mentioned each subimage is merged into an optimized image by image composing unit, and exports after being merged by all optimized images.
Further, described optimization process unit comprises at least two kinds in image smoothing filtrator, boundary detector, border booster, grayscale contrast's booster, Hi-pass filter, feature extractor.
Further, the assembly extracted in described feature extractor comprises the border of organ in subimage, tissue, the structure of organ, tissue or the structure of diseased tissue, border.
Further, described pretreatment unit, optimization process unit and image composing unit are formed by the element in programming, combination FPGA.
Advantage of the present invention: effectively can improve medical supersonic scan image quality; Can remove or reduce speckle noise, strengthening organ organizational boundary, improve spatial resolution and strengthen contrast.
Further, the diasonograph scan image optimized treatment method that the present invention relates to is implemented by fpga chip, thus has the advantages such as integrated level is high, consumes resources is few, and travelling speed is fast, drastically increase its range of application, PC system or embedded system can be widely used in.
Accompanying drawing explanation
A kind of diasonograph scan image optimized treatment method treatment scheme schematic diagram that Fig. 1 provides for the embodiment that the present invention relates to.
The logical organization block diagram of a kind of diasonograph that Fig. 2 provides for the embodiment that the present invention relates to.
In a kind of ultrasound scan images optimized treatment method that Fig. 3 provides for the embodiment that the present invention relates to, in the Image semantic classification process related to, the image schematic diagram after the process of generation.
Embodiment
Below in conjunction with concrete drawings and Examples, the invention will be further described.
An embodiment of the invention provide a kind of diasonograph scan image optimized treatment method, and its treatment scheme refers to shown in Fig. 1.Scan image quality optimization disposal route of the present invention comprises the steps:
A, input scan image, and pre-service is carried out to described scan image, so that scan image is divided into some subimages;
B, the subimage after above-mentioned segmentation walked abreast and carries out required image optimization process, optimized subimage accordingly after each subimage optimization, and optimization subimage corresponding for described each subimage is merged into an optimized image;
C, all optimized image obtained above is merged after export.
Specifically as shown in Figure 1, the image that scanning obtains, before optimization process, can represent by function f (x, y).First, it can carry out pre-service; Secondly, that (optimization process unit comprises some optimization process subelements by optimization process unit, described optimization process subelement comprises optimization process subelement I, optimization process subelement II, optimization process subelement III ..., optimization process subelement N, quantity N can need to arrange according to actual treatment) be optimized process, finally, be then the optimized image being synthesized these optimization processes by image composing unit (Synthesizer), then export final image.At this moment the final image exported compares the image of untreated input before, and picture quality promotes a lot, and uses function g(x, y) represent.
As shown in Figure 2, an embodiment of the invention provide a kind of diasonograph, and it comprises image optimization treating apparatus, and this image optimization treating apparatus includes fpga chip, for implementing the optimized treatment method of the ultrasound scan images that the present invention relates to.Also embedded system chip is comprised, to form Embedded diasonograph in diasonograph of the present invention.
In the present invention, diasonograph uses FPGA(Field-Programmable Gate Array) chip, utilize FPGA make its can with various operating system with the use of.Such as, the embedded chip system that integrated level is high, the combination of both can be completely achieved the portable function of diasonograph, and also can not lose machine performance simultaneously, takies the hardware resource that machine is too many.Certainly, in other embodiments, it also can be combined with PC system.
Further, according to the function of fpga chip, in conjunction with the ultrasound scan images optimized treatment method that the present invention relates to.By the mode of programming, the element in fpga chip is marked off three unit: pretreatment unit, optimization process unit and image composing unit.Each unit correspondence performs the corresponding steps in the image optimization disposal route that the present invention relates to.The various programming modes that pretreatment unit, optimization process unit and image composing unit can be suppressed by industry, are obtained by the element in combination FPGA; Wherein selectable programming mode includes but not limited to Verilog language, VHDL(Very-High-Speed Integrated Circuit HardwareDescription Language) language etc.
Wherein pretreatment unit is by the scan image of input, according to scan image size and the first predetermined ratio, scan image is expanded, its result refers to shown in Fig. 3, wherein be positioned at the picture element of original input image boundary member, can according to the first preset ratio, the mode adopting border to map, outwards expands.Image after expansion, can be divided into some subimages according to the second predetermined ratio, in order to the optimization process of follow-up subordinate phase.In Fig. 3,10 represent former scan image, and 20 represent the image after being expanded with border mapping mode by former scan image 10 according to the first predetermined ratio.According to the second predetermined ratio by amplify after Iamge Segmentation time, splitting the image obtained can be equal-specification (described specification comprises the parameter of size etc.), also can be not equal-specification, again or the combination of two kinds of specifications, specifically can need to arrange according to the type of scan image and actual treatment.Such as, the Iamge Segmentation after expanding is obtained 6 subimages, and described 6 subimages comprise the specification type of size in 3, and often kind of a specification type has two subimages.
Optimization process unit receives after the subimage of pretreatment unit process, according to default optimization process mode, described default optimization process mode includes but not limited to, drawing is level and smooth, frontier probe, border strengthen, and feature extraction, to these subimages be partitioned into, the parallel image optimization process carrying out these preset functions, finally, according to the quantity of parallel optimization processing mode, obtain the subimage of respective number.Namely each subimage will be optimized process through above-mentioned optimization process mode, and the subimage that each optimization process has is left optimization subimage, optimizes the quantity of subimage consistent with the kind of the optimization process mode in optimization process unit.These are through the subimage of each optimization process mode process, and all can be retained and store, the subimage then after these single optimizations, synthesizing an optimized image, optimized image is corresponding with each subimage.After by the image processing and tracking unit of each subimage after optimization process, obtain some optimized images, the quantity of optimized image is consistent with the quantity splitting the subimage obtained, then optimized image can continue to use in an in the end step Images uniting process.
In this visual optimization process, in one embodiment, pretreatment unit, optimization process unit and image composing unit obtain in fpga chip, optimization process unit in fpga chip, by programming, form corresponding functional module in conjunction with the element in fpga chip, such as, image smoothing filtrator (Smoothing Filter), boundary detector (Edge Detector), border booster (Edge Enhancer), Contrast enhanced device (Contrast Enhancer), Hi-pass filter (High-pass Filter), in feature extractor (feature extractor) etc. at least two kinds, to perform corresponding optimization process function accordingly.
After image composing unit receives the whole optimized images after optimization process cell processing, adopt the mode of nonlinear weight synthesis, synthesize these subimages, and then form last output image.In this nonlinear weight building-up process, relate to the parameter of use, can be the difference according to ultrasound scan objective, and adopt different setting weighting parameters.The parameter of concrete use, can according to actual needs, specifically set, and unrestrictedly.
Such as, original input image is split into 4 subimages at pretreatment stage by preset parameter, each subimage is after parallel optimization process, and each subimage can obtain some optimization subimages, and the optimization subimage that then each subimage is corresponding can synthesize 1 final optimization pass image.4 subimages be partitioned into like this, after parallel optimization process, finally or only can form 4 final optimization pass images.In synthesis step, these 4 final optimization pass images, can calculate last optimized image with following nonlinear weight composite formula:
G=a
1F
1+a
2F
2+a
3F
3 2+a
4F
4 3
Wherein, G is the output image after optimized image synthesis, F
1, F
2, F
3, F
4optimization figure after representing optimized merges, a
1, a
2, a
3, a
4represent weighting coefficient.Above-mentioned weighting coefficient, generally between-1 and+1, meets following condition simultaneously:
a
1+a
2+a
3+a
4=1
When above-mentioned comprise multiple weighting coefficient time, multiple weighting coefficient still will meet above-mentioned equilibrium relationships.
Such as, for the scan image that heart scanning obtains, it is in nonlinear weight synthesis, the parameter of employing, and the image that may obtain with scanning liver, the nonlinear weight parameter of employing is different.
The above; be only the embodiment in the present invention; but protection scope of the present invention is not limited thereto; any people being familiar with this technology is in the technical scope disclosed by the present invention; the conversion or replacement expected can be understood; all should be encompassed in and of the present inventionly comprise within scope, therefore, protection scope of the present invention should be as the criterion with the protection domain of claims.
Claims (2)
1. a diasonograph scan image quality optimization disposal route, is characterized in that, described scan image quality optimization disposal route comprises the steps:
(a), input scan image, and pre-service is carried out to described scan image, so that scan image is divided into some subimages;
(b), the subimage after above-mentioned segmentation walked abreast and carries out required image optimization process, optimized subimage accordingly after each subimage optimization, and optimization subimage corresponding for described each subimage be merged into an optimized image;
(c), all optimized image obtained above is merged after export;
In described step (a), when pre-service is carried out to scan image, scan image is amplified according to the first predetermined ratio, and the image after amplification is divided into the subimage of more than 3 or 3 according to the second predetermined ratio;
The described specification of subimage that is divided into is equal-specification or one or both not in equal-specification;
In described step (a), scan image is amplified with border mapping mode under the first predetermined ratio;
In described step (b), to the subimage be divided into be optimized processing mode comprise that drawing is level and smooth, border strengthens or GTG than at least two kinds in strengthening; The be optimized quantity of subimage of each subimage is consistent with the optimization process mode type of employing;
In described step (c), by nonlinear weight, optimized image is merged.
2. a diasonograph scan image quality optimization treating apparatus, is characterized in that: comprise pretreatment unit, and described pretreatment unit is connected with optimization process unit, and described optimization process unit is connected with image composing unit; Pretreatment unit is to scan image pre-service, and pretreated Iamge Segmentation is become some subimages, above-mentioned subimage walks abreast and carries out required image optimization process by optimization process unit, to obtain the optimization subimage of respective numbers after making each subimage optimization; The optimization subimage of above-mentioned each subimage is merged into an optimized image by image composing unit, and exports after being merged by all optimized images;
Described optimization process unit comprises at least two kinds in image smoothing filtrator, boundary detector, border booster, grayscale contrast's booster, Hi-pass filter, feature extractor;
The assembly extracted in described feature extractor comprises the border of organ in subimage, tissue, the structure of organ, tissue or the structure of diseased tissue, border;
Described pretreatment unit, optimization process unit and image composing unit are formed by the element in programming, combination FPGA.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210205578.1A CN102800072B (en) | 2012-06-20 | 2012-06-20 | Diasonograph scan image quality optimization disposal route and device thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210205578.1A CN102800072B (en) | 2012-06-20 | 2012-06-20 | Diasonograph scan image quality optimization disposal route and device thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102800072A CN102800072A (en) | 2012-11-28 |
| CN102800072B true CN102800072B (en) | 2015-07-29 |
Family
ID=47199171
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210205578.1A Active CN102800072B (en) | 2012-06-20 | 2012-06-20 | Diasonograph scan image quality optimization disposal route and device thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102800072B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105227802B (en) * | 2015-09-29 | 2018-06-29 | 深圳大学 | A kind of self-adaptation control method quickly scanned towards best quality image and system |
| CN107358177A (en) * | 2017-06-27 | 2017-11-17 | 维拓智能科技（深圳）有限公司 | A kind of medium and long distance pedestrian detection method and terminal device based on graphical analysis |
| CN110490891A (en) * | 2019-08-23 | 2019-11-22 | 杭州依图医疗技术有限公司 | The method, equipment and computer readable storage medium of perpetual object in segmented image |
| WO2021120071A1 (en) * | 2019-12-18 | 2021-06-24 | 深圳迈瑞生物医疗电子股份有限公司 | Ultrasonic imaging method, ultrasonic imaging system, and computer-readable storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101576994A (en) * | 2009-06-22 | 2009-11-11 | 中国农业大学 | Method and device for processing remote sensing image |
| CN101606854A (en) * | 2009-06-10 | 2009-12-23 | 无锡祥生科技有限公司 | A kind of high-precision real-time ultrasonic image scan conversion method |
| CN101897600A (en) * | 2009-05-26 | 2010-12-01 | 通用电气公司 | The system and method that is used for automatic ultrasound image optimization |
| EP2138102B1 (en) * | 2008-06-26 | 2011-09-28 | Samsung Medison Co., Ltd. | Formation of an enhanced elastic image in an ultrasound system |
-
2012
- 2012-06-20 CN CN201210205578.1A patent/CN102800072B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2138102B1 (en) * | 2008-06-26 | 2011-09-28 | Samsung Medison Co., Ltd. | Formation of an enhanced elastic image in an ultrasound system |
| CN101897600A (en) * | 2009-05-26 | 2010-12-01 | 通用电气公司 | The system and method that is used for automatic ultrasound image optimization |
| CN101606854A (en) * | 2009-06-10 | 2009-12-23 | 无锡祥生科技有限公司 | A kind of high-precision real-time ultrasonic image scan conversion method |
| CN101576994A (en) * | 2009-06-22 | 2009-11-11 | 中国农业大学 | Method and device for processing remote sensing image |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102800072A (en) | 2012-11-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| DE102016108737B4 (en) | Knowledge-based ultrasound image enhancement | |
| Napolitano et al. | Sound speed correction in ultrasound imaging | |
| JP5591440B2 (en) | Medical image display device | |
| CN102800072B (en) | Diasonograph scan image quality optimization disposal route and device thereof | |
| JP2007512862A (en) | Method of automatic multidimensional intravascular ultrasound image segmentation | |
| DE102010061577A1 (en) | Method and system for processing ultrasound data | |
| DE102016107222A1 (en) | Acquisition control for mixed mode ultrasound imaging | |
| CN104166974B (en) | CT locating film image enhancing method and CT locating film image enhancing device | |
| CN109589141A (en) | A kind of ultrasound diagnosis assisting system, system and ultrasonic diagnostic equipment | |
| CN106600550A (en) | Ultrasonic image processing method and system | |
| CN105073020A (en) | Ultrasonic diagnostic device and ultrasonic image processing method | |
| Cau et al. | Potential role of artificial intelligence in cardiac magnetic resonance imaging: can it help clinicians in making a diagnosis? | |
| CN108510489A (en) | A kind of pneumoconiosis detection method and system based on deep learning | |
| CN109003280A (en) | Inner membrance dividing method in a kind of blood vessel of binary channels intravascular ultrasound image | |
| CN107358594A (en) | Galactophore image processing system and method based on X ray and ultrasonic examination | |
| CN109965905A (en) | A kind of radiography region detection imaging method based on deep learning | |
| Kim et al. | Co-registration of speech production datasets from electromagnetic articulography and real-time magnetic resonance imaging | |
| Zhang et al. | Boundary delineation in transrectal ultrasound image for prostate cancer | |
| CN101322650A (en) | Ultrasound pattern display method | |
| CN103126721A (en) | Method and device for compound ultrasonic imaging based on multiple focuses and multiple ultrasonic velocities | |
| US20230305126A1 (en) | Ultrasound beamforming method and device | |
| CN116168097A (en) | Method, device, equipment and medium for constructing CBCT sketching model and sketching CBCT image | |
| CN112967295B (en) | Image processing method and system based on residual network and attention mechanism | |
| JP2019118694A (en) | Medical image generation apparatus | |
| CN111462065B (en) | Breast cancer detection method and system by means of ultrasonic and infrared sequence image fusion |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: The Yangtze River Road 214028 Jiangsu city of Wuxi Province, the new Industrial Park Wu District Five period of 51, No. 53, block No. 228 Patentee after: Wuxi CHISON medical Polytron Technologies Inc Address before: 214142 Jiangsu Province, Wuxi new area, Shannon Road No. 8 Patentee before: Xiangsheng Medical Image Co., Ltd., Wuxi |